#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import os
import matplotlib.pyplot as plt
from pathlib import Path
from IPython import display
import glob
from PIL import Image
import matplotlib.animation as animation
from src import waymo_training_math_tools as math_tool
from src import waymo_training_plot_tools as plot_tool
from src.waymo_transfer_training_to_tf import *
from src.waymo_training_math_tools import *

data_path='/home/mdmp/ppp/trajectory-prediction/dataset/uncompressed_scenario_training_training.tfrecord-00510-of-01000'
#waymo_dataset_file11='/home/mdmp/prpproject/WOMD_Dataset/training_dataset/uncompressed_scenario_training_training.tfrecord-00004-of-01000'



waymo_dataset_list = []

waymo_dataset_list.append(data_path)
#waymo_dataset_list.append(waymo_dataset_file11)



generate_individual_images = True
generate_animation = True

def main():    
   dataloader = Dataloader(data_path)
   # map_feature_list = dataloader.get_map_feature_list()
   around_cars = get_around_cars_byID(1039)
   
   print(around_cars)
   # for key in d:
   #    print(key)
   #    print(d[key][0][0])
  
   #print(dir(dict[84]))
   
   # print(dict[84].right_neighbors_id_dict)

   # print(len(map_feature_list))
   # for i in range(len(map_feature_list)):
   #    print(type(map_feature_list[i]))
   # print(map_feature_list[10].line_id)
   # pre_id_list = dataloader.get_all_car_id_list()
   # print(pre_id_list)
   #plot_tool.visualization(data_path,dataloader,None, None,11,90,True,True)
        

if __name__ == "__main__":
    main()